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Metadata only record Scaling up conservation agriculture production systems (CAPS) for smallholders requires LTRA-10 (CAPS for smallholder farms in eastern Uganda and western Kenya)

This study seeks to understand the pathway by which new technology and the associated knowledge passes through community networks in western Kenya and eastern Uganda. Previous research in the region emphasizes the importance of community support to promote widespread adoption of Conservation Agriculture practices. We will simulate complex contagions of information in these networks using the simulation platform EpiSimdemics. This work complements and expands on the growing body of research that uses network analysis to study the effects of network structure and social contagion on complex health and social systems. LTRA-10 (CAPS for smallholder farms in eastern Uganda and western Kenya)

The poster presents social network analysis as a method to support collaboration in the participatory research process to design strategies to scale up conservation agriculture production systems (CAPS). Objectives of this research project were to identify knowledge and attitudes concerning agricultural production practices held by actors in the network, to describe the structure of information and physical resource flows between these actors, and to determine critical pathways and opinion leaders that facilitate technological change among farmers and their service sector providers. Research presented was carried out in Eastern Uganda and Western Kenya. The poster highlights the feedback provided by farmers during workshops held in four communities. Both scientific and local knowledge were found in the research communities. Findings identified misconceptions about agent misconceptions about the knowledge of others. Findings also identified challenges to conservation agriculture adoption and how local networks can be mobilized to resolve them. Social Network Analysis contributions to overall project management were also presented. The research verified and expanded the network of service sector/community agents involved in the project, encouraged reflexivity in the research process, and empowered project participants to address network conditions which they can control. LTRA-10 (CAPS for smallholder farms in eastern Uganda and western Kenya)

This presentation describes the Technology Networks Cross Cutting Research Activity (CCRA-8) and the baseline survey module to be incorporated by the LTRA teams. The Technology Networks CCRA has three key objectives: 1) Reveal local network structures 2) Identify different technological frames for agricultural production and 3)Determine key actors and knowledge pathways to facilitate innovation. Data will be collected through the integration of an additional module into SANREM baseline surveys conducted by the LTRA teams which incorporates a set of Likert scale questionnaire items and a network module to measure relations between actors according to frequency, trust, and resources exchanged. The module also collects data on soil perceptions and practices and participation by men and women in agricultural activities. CCRA-8 (Technology Networks for Sustainable Innovation)

In studying agricultural development, we are interested in the characteristics of local contexts which enable or prevent technological change. Network theory and literature from social construction of technology provide numerous methods to make these complex processes of change more transparent. In this paper, we explore how these different approaches can inform conceptualizations of technological change in agriculture through 1) a brief synthesis of the network and social construction of technology literature; 2) a review of technological change in agricultural experiences; and 3) the proposal of a refined research methodology. Upon examining the literature, the distinction between structural and semiotic networks and the concept of technological frame are particularly valuable. Conceptualizing technological change through a social construction of technology approach, we are interested in the fundamental question of how and why a particular technological frame becomes dominant. We argue that this process unfolds through local network spaces and dynamics. In an attempt to illustrate the connection between network processes and technological frame adoption; we reinterpret two examples of technological change in agriculture. These include technology transfer in the Green Revolution and the emergence of adaptive management for the development of Conservation Agriculture production systems in the United States and Brazil. We find that the reformulation and reorganization of agricultural production networks are captured in Callon's moments of translation, where individuals take on new and even competing identities. Through deconstructing this process, we hope to provide the theoretical foundation for a more comprehensive research model to examine technological change in agriculture. CCRA-8 (Technology Networks for Sustainable Innovation)